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Record W4396777604 · doi:10.1101/2024.05.06.591106

Sex differences emerge after the menopause transition: Females show accelerated decline in episodic memory for spatial context at midlife

2024· preprint· en· W4396777604 on OpenAlexaff
Annalise Aleta LaPlume, Rikki Lissaman, Julia Kearley, Maria Natasha Rajah

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsMcGill UniversityToronto Metropolitan University
Fundersnot available
KeywordsEpisodic memoryPsychologyContext (archaeology)RecallCalifornia Verbal Learning TestCognitive declineCognitionDevelopmental psychologyDemographyAudiologyVerbal memoryCognitive psychologyMedicineDiseaseDementia

Abstract

fetched live from OpenAlex

Abstract Background and Objectives The ability to remember past events in rich contextual detail (episodic memory) declines with advancing age, with accelerated decline around midlife. Past research indicates there may be sex differences in cognitive aging trajectories and risk for age-related neurodegenerative diseases, i.e. Alzheimer’s Disease. Yet, little is known about how biological sex affects episodic memory in the adult lifespan. We examined age differences in episodic memory for spatial context in males and females. Research Design and Methods 192 adults aged 21 to 65 ( M =44, SD =13, 134 females) completed a face-location task measuring spatial context memory (correct spatial context retrieval rates) and facial item memory (correct recognition rates), and the California Verbal Learning Test version II (CVLT-II) measuring verbal item memory (long free recall, cued recall, and recognition rates). Changepoint regression analysis was used to estimate the slope of memory across age and any significant shifts in the slope (indicating critical transition periods). Results Regression analyses revealed that the best-fitting model for females on spatial context memory accuracy was a one-changepoint model, with gradual decline of 2% ( SE =1) fewer correct responses per year of age from age 21 until age 50 (95% CI 41, 58), shifting to more rapid decline of 4% ( SE =1) fewer correct responses per year of age until age 65. The best fitting model for males on spatial context memory accuracy was linear, with no significant changes across ages. The best fitting models for both sexes were linear for facial item memory accuracy, spatial context memory and facial item memory reaction times, and verbal item memory accuracy. Discussion and Implication Males and females show similar decline on spatial context memory from young adulthood until midlife, after which females show greater decline than males. Importantly, disaggregating by sex indicated that past midlife effects on episodic memory for context may be driven by a specific group of females (post-menopausal), as accelerated decline occurred at the same time as menopause in midlife females and did not occur in midlife males. Translational Significance Problem Addressed We use changepoint regression to examine how biological sex influences age differences in remembering the context of past events (episodic memory). Main outcome Females, but not males, showed significantly greater decline on spatial context memory (i.e., correctly recalling the location of previously learned information) after age 50, which aligns with the time of menopause in midlife females. Implications for Translation Episodic memory for spatial context shows accelerated decline in females after midlife compared to before midlife, but not in midlife males, indicating the potential influence of menopause on aging of memory.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.269
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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